Self-consumption
PV surplus is stored. When needed, the battery supplies the building.
HYD.OS · Energy Management System
HYD.OS. The energy management that thinks in hydrogen.
Battery, PV, electrolyser, HIVE storage and fuel cell — one system, one schedule, one interface. HYD.OS measures, forecasts and controls every energy flow on site. Hydrogen is not a special installation here; it is the extension of your battery.
Live demo
One day with HYD.OS.
From midnight to midnight, price, sun and load keep changing — HYD.OS decides every 15 minutes where the energy goes.
6.0kW flow
0.0 kWPV systemStandby
0.0 kWBattery35.0 % · Idle
6.0 kWGridImport
6.0 kWConsumers
0.0 kWElectrolyserStandby
0.0 kWHIVE storage40.0 % · Idle
0.0 kWFuel cellStandby
40 %Fill level
Self-sufficiency0 %
Self-consumption–
Storage35.0 %
Idle
Grid6.0 kWImport
Schedule
Time00:00Operating modeHold
Purchase priceFeed-in priceState of chargeH₂ fill level
Example scenario, not a measurement — every value is physically consistent.
Schedule
The schedule builds itself.
The system automatically creates a schedule for the battery storage. It takes into account electricity prices, expected PV generation, consumption, state of charge and configured power limits. The schedule is updated regularly.
Electricity prices
Dynamic purchase and feed-in prices, every 15 minutes.
Expected PV generation
Forecast from weather data for the site.
Consumption
Load profile from measured days.
State of charge
Battery and HIVE fill level in real time.
Power limits
Grid connection, inverter, electrolyser.
The intelligence behind it
How HYD.OS computes the schedule.
No fixed rulebook, but forecasting and optimisation: HYD.OS predicts generation, consumption and prices, simulates millions of possible schedules and picks the cost-optimal one — fresh every quarter hour.
- 01
Forecast
Four forecasting models predict the coming hours from weather data, measured load profiles and electricity prices — among them a neural network for time series. State of charge and the plant's power limits are added.
- 02
Simulate
An evolutionary optimisation runs on the order of 47 million operating scenarios every quarter hour: when to charge, when to discharge, when to make hydrogen, when to sell. Every scenario is scored on cost and security of supply.
- 03
Decide
The best scenario becomes the schedule: one operating mode per quarter hour for battery, electrolyser and fuel cell. When price, weather or load change, HYD.OS recomputes — continuously, without intervention.
4forecasting models, including a neural network
47Msimulated scenarios per quarter hour
41quarter hours of planning horizon
15minschedule refresh
Figures from live operation of the HydroSolid reference plant, as of July 2026.
Operating modes
Seven operating modes. One decision every quarter hour.
For each time window HYD.OS picks the mode that cuts cost and secures supply — the demo above shows which one is active right now.
Delay discharge
Energy is kept for later, for example for expensive hours.
Charge from grid
At low prices the battery can be charged from the grid.
Discharge to grid
At attractive feed-in prices energy from the battery can be sold.
Peak shaving
The battery reduces high power peaks in grid consumption.
Hold
The state of charge is kept as constant as possible.
Off
No price-dependent control by this schedule.
The difference
Hydrogen as the extension of the battery.
A battery shifts energy by hours. Hydrogen shifts it by days and weeks. HYD.OS treats both as one storage with two time horizons: surplus the battery can no longer absorb goes to the electrolyser and fills the HIVE. When energy is short, the battery discharges first, then the fuel cell supplies.
Battery
HoursTime horizon
Fast and efficient — balancing day and night.
HIVE storage
WeeksTime horizon
Solid-state storage with RSH2, 0.9 to 500 kg H₂, only 35 bar working pressure.
Fuel cell
24/7Re-electrification
Supplies power when sun and battery are not enough — including off-grid.
Connectable
Open to your plant. Proven in industry.
HYD.OS builds on an industry-proven core and speaks Modbus, M-Bus, MQTT and OCPP. The edge device keeps controlling on site even when the cloud is unreachable; the portal monitors, configures and updates remotely.
19Meter manufacturers natively supported
20+Inverter and storage manufacturers
13Electricity price and tariff integrations
58Controllers, from self-consumption to peak shaving
- Forecasts from weather data and measured load profiles
- Day-ahead electricity prices, e.g. ENTSO-E, aWATTar, Tibber
- Live view and history: self-sufficiency, self-consumption, generation, consumption, storage
- Remote maintenance, remote update and alerting per site
One portal, many sites
Many sites. One system.
HYD.OS separates control from oversight: on site, every location runs autonomously on its edge device, even without the cloud. In the portal you create as many sites as you need, assign users and roles per site, and monitor, configure and update all of them remotely.
Readings to the portalUpdate to the siteAlert
Example sites with example values, not a measurement.
- One portal, roles per siteCreate sites, invite users and assign roles per site, from guest to administrator — one sign-in for all sites.
- Remote configuration and remote updateSet up components and the network of the edge device from the portal; roll out system updates, restarts and function packages per site.
- Alerting per user and siteNotifications configured per user, a traffic-light status per device and controller, metrics to Prometheus for your own monitoring.
- History across all sites, open interfaceDaily to yearly figures per site, time series aggregated across many sites, Excel export — plus a backend-to-backend interface for live data across sites.
Multi-site optimisationIn development
What we are building nowIn development In development In use
From schedule to digital twin.
Digital twin of the site
A virtual replica of generation, load and storage on which HYD.OS rehearses decisions in advance.
Multi-site optimisation
Plan and control several sites as one pool.
Self-learning forecasts
Load-profile clustering and neural networks keep refining the prediction.
See HYD.OS at your site.
We show you the schedule for your load and generation curve — with battery, with hydrogen, or both.